R
Lead AI Engineer
R
Lead AI Engineer
r3 consultant8-12 Years
This job is no longer accepting applications
Job Description
Job Title: Lead AI Engineer
Location: Bangalore
Work Mode: Onsite / WFO
Experience: 8–12 years
Education: Bachelor's/Master's in Computer Science, Engineering, or related field (M.Tech/MS preferred but not mandatory)
Budget/CTC: Up to ₹40 LPA
Notice Period: 30 days preferred
Roles & Responsibilities
Lead end-to-end AI solution development — from architecture design through production deployment
Own AI system design with a strong emphasis on LLMs and Retrieval-Augmented Generation (RAG)
Drive creation of comprehensive POCs and data-driven AI strategies for client/business problems
Guide cross-functional teams (data engineers, ML engineers, product) and manage stakeholder expectations across Pharma, Retail, or CPG domains
Own technical decision-making on model selection, RAG architecture, cloud infrastructure, and MLOps practices
Mentor and upskill junior/mid-level AI engineers
Present AI strategy and solution trade-offs to both technical and business stakeholders
Mandatory Skills
Python, SQL
AI system design & end-to-end AI solution development (LLMs & RAG)
Cloud platforms — Azure / AWS / GCP
Data & AI solutioning (data pipelines feeding AI systems)
8–12 yrs total experience with demonstrable lead-level ownership of AI projects
Good to Have
Domain experience in Pharma, Retail, or CPG
End-to-end POC development experience
Leadership in AI project delivery (team lead/manager track record)
MLOps / CI-CD practices for AI pipelines
Must-Have Soft Skills
Leadership and people management
Strategic thinking and decision-making
Stakeholder management
Effective communication (technical ↔ non-technical)
Good-to-Have Soft Skills
Mentoring and coaching junior team members
Ability to convey complex domain concepts to mixed audiences
Location: Bangalore
Work Mode: Onsite / WFO
Experience: 8–12 years
Education: Bachelor's/Master's in Computer Science, Engineering, or related field (M.Tech/MS preferred but not mandatory)
Budget/CTC: Up to ₹40 LPA
Notice Period: 30 days preferred
Roles & Responsibilities
Lead end-to-end AI solution development — from architecture design through production deployment
Own AI system design with a strong emphasis on LLMs and Retrieval-Augmented Generation (RAG)
Drive creation of comprehensive POCs and data-driven AI strategies for client/business problems
Guide cross-functional teams (data engineers, ML engineers, product) and manage stakeholder expectations across Pharma, Retail, or CPG domains
Own technical decision-making on model selection, RAG architecture, cloud infrastructure, and MLOps practices
Mentor and upskill junior/mid-level AI engineers
Present AI strategy and solution trade-offs to both technical and business stakeholders
Mandatory Skills
Python, SQL
AI system design & end-to-end AI solution development (LLMs & RAG)
Cloud platforms — Azure / AWS / GCP
Data & AI solutioning (data pipelines feeding AI systems)
8–12 yrs total experience with demonstrable lead-level ownership of AI projects
Good to Have
Domain experience in Pharma, Retail, or CPG
End-to-end POC development experience
Leadership in AI project delivery (team lead/manager track record)
MLOps / CI-CD practices for AI pipelines
Must-Have Soft Skills
Leadership and people management
Strategic thinking and decision-making
Stakeholder management
Effective communication (technical ↔ non-technical)
Good-to-Have Soft Skills
Mentoring and coaching junior team members
Ability to convey complex domain concepts to mixed audiences
More Info
Key Skills
About Company
Skills:
Java, Kafka, Spring Boot, Datadog, Redis, Postgres, Helm, Kubernetes, AWS, LangChain, LangGraph, Temporal
Skills:
Java, Kafka, Spring Boot, Datadog, Redis, Postgres, Helm, Kubernetes, AWS, LangChain, AI agent engineering, LangGraph, Temporal
Skills:
isolation), vLLM), Open-source LLMs (Ollama, Security fundamentals (auth, Cloud deployment, Docker, FastAPI, Python, LangChain, Re-ranking models, Vector databases, LangGraph, secrets, Voice AI pipelines, Hybrid search, CI/CD, RAG pipelines, Multi-agent systems, LlamaIndex
Skills:
Computer Vision, Opencv, Pytorch, Python, Speechmatics, Azure Cognitive Services, Mask R-CNN, DINO, torchaudio, Audio Speech Processing, Wav2Vec, CLIP, ASR models, Rapid Prototyping, Image Pipelines, YOLO, Librosa, Vision Transformers, Whisper
Skills:
production deployment , Tensorflow, Pytorch, Python, Version Control, Application Architecture, System Design, Containers, orchestration technologies, AI ML applications, CI CD, observability tools, code review practices, evaluation frameworks, LangChain, operational monitoring, Documentation, deep learning frameworks, retrieval-augmented generation, Semantic Kernel, Production Support, agent development patterns, performance optimization, model APIs, cloud ML platforms, prompt orchestration, LlamaIndex